TAZI’s ML platform enabled reducing the frequency of regular maintenance by predicting failures or anomalies in advance and avoiding unnecessary maintenance costs.
Customers want to use sensor data to predict machine failures in advance to reduce costs. TAZI ML algorithms not just helped to predict machine failures beforehand but also provided detection of which sensor data have critical importance.
In this particular example, medical cabinet lock failure causes customer dissatisfaction and also high maintenance costs. TAZI ML platform is used to predict lock failures in advance so that predictive actions can be taken before the lock failure happens.